The tools and technology required to automate the process of generating a company’s financial data grow everyday.&nbsp;The challenge is that you cannot&nbsp;fully&nbsp;automate what humans are so heavily influenced to manipulate.&nbsp;For so long as fortunes are tied to financial performance, there will be examples of exaggerated financial performance. Accounting, often referred to as the language of business, is not a simple language. Under GAAP the rules detailing how revenue should be recorded exceed 700 pages of painfully dense text. [1] Consequently, the quality of revenue between two firms in the same industry can vary substantially.

Amazon, for example, has convinced its customers to pay immediately and its suppliers to wait months for payment. The result is a pool of cash at the company’s disposal. Barron’s described it as follows:

In some ways, Amazon is like Berkshire Hathaway, but with better returns.&nbsp;Berkshire sells insurance, where premium payments roll in long before claims are paid, allowing CEO Warren Buffett to invest other people’s capital free of charge. Amazon sells inventory so quickly that it often collects from customers before it pays suppliers, creating an ongoing free float of cash to use. [2]

In stark contrast, Conn’s (another retail business that was demonstrating strong growth) had a very different model that made sales a poor metric for success:

Very simplistically, two things happen at a Conn’s store: Merchandise walks out of the building and dollar bills walk in. The rate of change in merchandise walking out is what counts in the comp stores’ data. It’s the metric that was up by the amazing, aforementioned 32% in November, and by 23.7% in the first nine months.

Short sellers focus more on the rate of growth of dollar bills walking in.&nbsp;The essential bear story is that the rate at which these dollars are walking into Conn’s locations this year is largely unchanged, surging comps and new-store openings notwithstanding. So something is wrong with this picture.&nbsp;Essentially, Conn’s is giving people merchandise and telling them they don’t have to pay for it just yet, or they can pay for it slowly, or the company can restructure their loans, etc.&nbsp;With same-store comps rising by double-digits and with 10% to 15% more locations this year than last, cash revenues are essentially flat.&nbsp;What’s financed this scorching growth is customer receivables.&nbsp;[3]

This is a simple example that any entry-level analyst or automated financial modeling software could identify, but I thought it would help illustrate a point:&nbsp;Revenue is the first line item on an income statement, and typically a starting point in most financial models, without even beginning to evaluate the line items that follow, substantial analysis may already be required.

The additional challenge is that investors&nbsp;want&nbsp;to believe success stories. People like to get rich, and if you can craft a narrative outlining a path to riches many will pile in. Sometimes it’s not even that difficult, in hindsight, to identify the red flags that should have generated some level of uneasiness. Sticking with revenue and using Enron’s growth as an example, authors Schilit and Perler make an entertaining observation:

Curious investors might have questioned how frequently companies tend to grow their&nbsp;revenue&nbsp;from under $10 billion to over $100 billion in five years.&nbsp;The answer: never.

Even though entire industries exist to validate the financial information prepared by businesses, there are still regular examples of fraud. It makes understanding how a business creates or consumes cash an essential skill set,* and while the tools to complete this analysis will continue to multiply, it will forever be a good idea to evaluate the data yourself.

This questionoriginally appeared on Quora – the place to gain and share knowledge, empowering people to learn from others and better understand the world. You can follow Quora on Twitter, Facebook, and Google+. More questions:

The tools and technology required to automate the process of generating a company’s financial data grow everyday.The challenge is that you cannotfullyautomate what humans are so heavily influenced to manipulate.For so long as fortunes are tied to financial performance, there will be examples of exaggerated financial performance. Accounting, often referred to as the language of business, is not a simple language. Under GAAP the rules detailing how revenue should be recorded exceed 700 pages of painfully dense text. [1] Consequently, the quality of revenue between two firms in the same industry can vary substantially.

Amazon, for example, has convinced its customers to pay immediately and its suppliers to wait months for payment. The result is a pool of cash at the company’s disposal. Barron’s described it as follows:

In some ways, Amazon is like Berkshire Hathaway, but with better returns. Berkshire sells insurance, where premium payments roll in long before claims are paid, allowing CEO Warren Buffett to invest other people’s capital free of charge. Amazon sells inventory so quickly that it often collects from customers before it pays suppliers, creating an ongoing free float of cash to use. [2]

In stark contrast, Conn’s (another retail business that was demonstrating strong growth) had a very different model that made sales a poor metric for success:

Very simplistically, two things happen at a Conn’s store: Merchandise walks out of the building and dollar bills walk in. The rate of change in merchandise walking out is what counts in the comp stores’ data. It’s the metric that was up by the amazing, aforementioned 32% in November, and by 23.7% in the first nine months.

Short sellers focus more on the rate of growth of dollar bills walking in.The essential bear story is that the rate at which these dollars are walking into Conn’s locations this year is largely unchanged, surging comps and new-store openings notwithstanding. So something is wrong with this picture.Essentially, Conn’s is giving people merchandise and telling them they don’t have to pay for it just yet, or they can pay for it slowly, or the company can restructure their loans, etc.With same-store comps rising by double-digits and with 10% to 15% more locations this year than last, cash revenues are essentially flat.What’s financed this scorching growth is customer receivables.[3]

This is a simple example that any entry-level analyst or automated financial modeling software could identify, but I thought it would help illustrate a point:Revenue is the first line item on an income statement, and typically a starting point in most financial models, without even beginning to evaluate the line items that follow, substantial analysis may already be required.

The additional challenge is that investorswantto believe success stories. People like to get rich, and if you can craft a narrative outlining a path to riches many will pile in. Sometimes it’s not even that difficult, in hindsight, to identify the red flags that should have generated some level of uneasiness. Sticking with revenue and using Enron’s growth as an example, authors Schilit and Perler make an entertaining observation:

Curious investors might have questioned how frequently companies tend to grow theirrevenuefrom under $10 billion to over $100 billion in five years.The answer: never.

Even though entire industries exist to validate the financial information prepared by businesses, there are still regular examples of fraud. It makes understanding how a business creates or consumes cash an essential skill set,* and while the tools to complete this analysis will continue to multiply, it will forever be a good idea to evaluate the data yourself.

This questionoriginally appeared on Quora – the place to gain and share knowledge, empowering people to learn from others and better understand the world. You can follow Quora on Twitter, Facebook, and Google+. More questions: